基于高斯分布的自适应旁瓣相消零陷展宽算法

Null Broadening Algorithm for Adaptive Sidelobe Canceller Based on Gaussian Distribution

摘要:

无人机的高动态特性,导致干扰信号来波方向与自适应旁瓣相消算法(ASLC)生成的零陷位置不匹配,这一现象直接降低了ASLC系统的抗干扰效能。针对这一问题,将基于高斯分布的锥化矩阵零陷展宽算法融入ASLC技术中,旨在解决高动态环境下干扰信号来波方向与零陷失配的问题。通过假设干扰信号来波方向服从高斯分布,根据最小均方误差(MMSE)准则推导锥化后的自相关矩阵以及互相关矩阵解析式,仿真实验结果表明所提算法在-45dB零陷深度上零陷展宽宽度比均匀分布零陷展宽算法提高了21%。

Abstract:

The high dynamic characteristics of Unmanned Aerial Vehicle(UAV) result in null mismatch of Adaptive Sidelobe Cancellation (ASLC), which directly reduces the interference suppression effectiveness of the ASLC system. To address this issue, a Gaussian-distributed tapering matrix null broadening algorithm is integrated into the ASLC technology, aiming to solve the mismatch problem between the interference signal DOA and the null steer in high dynamic environments. By assuming that the DOA of the interference signal follows the Gaussian distribution, the tapered autocorrelation matrix and cross-correlation matrix are derived analytically based on the Minimum Mean Square Error (MMSE) criterion. Simulation results demonstrate that the proposed algorithm achieves a 20% increase in null broadening width at -50dB null depth compared to the uniform distribution null broadening algorithm.